Update README.md

README.md

@@ -1,12 +1,19 @@
 ---
-# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
-# Doc / guide: https://huggingface.co/docs/hub/model-cards
-{{ card_data }}
+'[object Object]': null
+license: mit
+language:
+- en
+library_name: adapter-transformers
+pipeline_tag: text-classification
 ---
 
-# Model Card for {{ model_id | default("Model ID", true) }}
+# Model Card for {{ orYx-models/finetuned-roberta-leadership-sentiment-analysis | default("orYx-models/finetuned-roberta-leadership-sentiment-analysis", true) }}
 
-<!-- Provide a quick summary of what the model is/does. -->
+<!-- This model is a finetuned version of, roberta text classifier.
+The finetuning has been done on the dataset which includes inputs from corporate executives to their therapist.
+The sole purpose of the model is to determine wether the statement made from the corporate executives is "Positive, Negative, or Neutral" with which we will also see "Confidence level, i.e the percentage of the sentiment involved in a statement.
+The sentiment analysis tool has been particularly built for our client firm called "LDS".
+Since it is prototype tool by orYx Models, all the feedback and insights from LDS will be used to finetune the model further.-->
 
 {{ model_summary | default("", true) }}
 
@@ -14,39 +21,47 @@
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+<!-- This model is finetuned on a RoBERTa-base model trained on ~124M tweets from January 2018 to December 2021, 
+and finetuned for sentiment analysis with the TweetEval benchmark.
+The original Twitter-based RoBERTa model can be found here and the original reference paper is TweetEval.
+This model is suitable for English. -->
 
 {{ model_description | default("", true) }}
 
-- **Developed by:** {{ developers | default("[More Information Needed]", true)}}
+- **Developed by:** {{ developers | default("[orYx Models]", true)}}
 - **Funded by [optional]:** {{ funded_by | default("[More Information Needed]", true)}}
-- **Shared by [optional]:** {{ shared_by | default("[More Information Needed]", true)}}
-- **Model type:** {{ model_type | default("[More Information Needed]", true)}}
-- **Language(s) (NLP):** {{ language | default("[More Information Needed]", true)}}
-- **License:** {{ license | default("[More Information Needed]", true)}}
-- **Finetuned from model [optional]:** {{ base_model | default("[More Information Needed]", true)}}
+- **Shared by [optional]:** {{ shared_by | default("[Vineedhar, relkino, kalhosni]", true)}}
+- **Model type:** {{ model_type | default("[Text Classifier]", true)}}
+- **Language(s) (NLP):** {{ language | default("[English]", true)}}
+- **License:** {{ license | default("[MIT]", true)}}
+- **Finetuned from model [optional]:** {{ base_model | default("[cardiffnlp/twitter-roberta-base-sentiment-latest]", true)}}
 
 ### Model Sources [optional]
 
-<!-- Provide the basic links for the model. -->
+<!--This is HuggingFace modelID - cardiffnlp/twitter-roberta-base-2021-124m-->
 
 - **Repository:** {{ repo | default("[More Information Needed]", true)}}
-- **Paper [optional]:** {{ paper | default("[More Information Needed]", true)}}
+- **Paper [optional]:** {{ paper | default("[TimeLMs - https://arxiv.org/abs/2202.03829]", true)}}
 - **Demo [optional]:** {{ demo | default("[More Information Needed]", true)}}
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+<!-- The Sentiment Analysis tool is made domain specific, however since it is a protoype, the depths into domain are still to be ventured.
+Use case: We can analyse the text from any executive, employee, client of an organization and attach a sentiment to it.
+ The outcomes of this will be a "Scored sentiment" upon which we can look for likeliness of an event occurring or vice versa.
+ The resultant scenario to this will be to generate a rating system based on the sentiments generated by texts from an entity.
+-->
 
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+<!-- You can infer the model at, orYx Models page, Leadership Sentiment Analyzer - spcace. 
+The Space id is - orYx-models/Leadership-sentiment-analyzer -->
 
-{{ direct_use | default("[More Information Needed]", true)}}
+{{ direct_use | default("orYx-models/Leadership-sentiment-analyzer", true)}}
 
 ### Downstream Use [optional]
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+<!-- This phase is under progress and will be shared once the model is deployed under larger ecosystem/.app -->
 
 {{ downstream_use | default("[More Information Needed]", true)}}
 
@@ -58,13 +73,13 @@
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+<!-- The model is sometimes prone to misinterpret the sentiments. -->
 
 {{ bias_risks_limitations | default("[More Information Needed]", true)}}
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+<!-- ]You can futher finetune the model to get better results. -->
 
 {{ bias_recommendations | default("Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.", true)}}
 
@@ -193,8 +208,8 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## Model Card Authors [optional]
 
-{{ model_card_authors | default("[More Information Needed]", true)}}
+{{ model_card_authors | default("[Vineedhar, relkino]", true)}}
 
 ## Model Card Contact
 
-{{ model_card_contact | default("[More Information Needed]", true)}}
+{{ model_card_contact | default("[https://khalidalhosni.com/]", true)}}